# A Short Note on a Variant of the Squint Algorithm

arXiv: https://arxiv.org/abs/2603.03409 · HTML: https://mlsanity.com/paper/2603.03409/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 2 of its 4 references that are in the map.
- First posted on arXiv 3 Mar 2026.

## Builds on (most cited first, 2 of 2)

- [Second-order Quantile Methods for Experts and Combinatorial Games](https://mlsanity.com/paper/1502.08009/) (2015)
- [A second order regret bound for NormalHedge](https://mlsanity.com/paper/2602.08151/) (2026)

## Built on by (most cited first, 1 of 1)

- [Adaptive Bayes exactly tracks information over intrinsic time](https://mlsanity.com/paper/2607.08789/) (2026)

## Abstract (arXiv)

This short note describes a simple variant of the Squint algorithm of Koolen and Van Erven [2015] for the classic expert problem. Via an equally simple modification of their proof, we prove that this variant ensures a regret bound that resembles the one shown in a recent work by Freund et al. [2026] for a variant of the NormalHedge algorithm [Chaudhuri et al., 2009].